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An EWMA Solution to Detect Shifts in a Bernoulli Process in an Out‐of‐control Environment
Author(s) -
Chakhunashvili Alexander,
Bergman Bo
Publication year - 2006
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.719
Subject(s) - ewma chart , control chart , statistical process control , bernoulli's principle , poisson distribution , process (computing) , normality , allowance (engineering) , bernoulli process , hypergeometric distribution , statistics , engineering , computer science , mathematics , reliability engineering , operations management , aerospace engineering , operating system
The Exponentially Weighted Moving Average (EWMA) control chart has mainly been used to monitor continuous data, usually under the normality assumption. In addition, a number of EWMA control charts have been proposed for Poisson data. Here, however, we suggest applying the EWMA to hypergeometric data originating from a multivariate Bernoulli process. The problem studied in this paper concerns the wear‐out of electronics testers resulting in unnecessary and costly reparations of electronic units. Assuming that the testing process is in statistical control, although the quality of the tested units is not, we can detect the wear‐out of a tester by finding assignable causes of variation in that tester. This reasoning forms the basis of a new EWMA procedure designed to detect shifts in a Bernoulli process in an out‐of‐control environment. Copyright © 2005 John Wiley & Sons, Ltd.